Improved Conjunction Analysis via Collaborative Space Situational Awareness T.S. Kelso & David A. Vallado, CSSI Joseph Chan & Bjorn Buckwalter, Intelsat Corporation

Pg 2 of 17 Overview Motivation Background Proposed Solution Analysis of Orbital Data Sources –Supplemental TLEs GPS, GLONASS, Intelsat Application: SOCRATES-GEO Summary & Conclusions

Pg 3 of 17 Motivation Recent events emphasize need for improved SSA for conjunction analysis –Chinese ASAT test (2007 Jan 11) –USA 193 intercept (2008 Feb 21) –ISS maneuver to avoid Cosmos 2421 debris (2008 Sep) Geostationary orbit (GEO) is a limited resource –More satellites = more conjunctions –Implications of a collision are significant Potential loss of colliding satellites and associated revenues Increase in debris, putting other satellites at risk

Pg 4 of 17 Background Conjunction analysis needs full-catalog orbital data –TLEs are currently the only such source Low accuracy results in high false-alarm rate More accurate orbital data could –Reduce false alarms –Improve use of limited tracking resources

Pg 5 of 17 Background Current system limited to non-cooperative tracking –SSN uses combination of radar and optical resources Operational satellites most difficult to track due to maneuvers –Maneuvers typically not known ahead of time –Delay in detecting maneuvers can result in poor accuracy or even ‘lost’ satellites –Requires more SSN resources to maintain orbits

Pg 6 of 17 Proposed Solution Satellite operators already maintain orbits –Active ranging, GPS can be very accurate Develop Data Center to collect operator data –Use operator data to improve conjunction analysis –Provide analysis/data to all contributors Current Data Center participation –Intelsat, Inmarsat, EchoStar, SES (Astra, New Skies, Americom), NOAA, Star One, Telesat –114 satellites—30% active GEO 24 satellites pending

Pg 7 of 17 Analysis of Orbital Data Sources Many sources of operator orbital data –Direct from satellite operator (Data Center) –Public sources GPS (almanacs, precise ephemerides) GLONASS (precise ephemerides) Intelsat (11-parameter data, ephemerides) NOAA, EUMETSAT (state vectors) Challenges –User-defined data formats –Variety of coordinate frames & time systems used

Pg 8 of 17 Supplemental TLEs Use public orbital data –GPS almanacs –GLONASS precise ephemerides –Intelsat 11-parameter data Import data into STK to generate ephemerides Generate TLE from ephemerides – –Allows users to see benefit Test cases with supporting data –Overcomes limitations in most orbital software

Pg 9 of 17 GPS Almanacs vs. TLEs Mean: km Max: km Mean: km Max: km

Pg 10 of 17 GPS Supplemental TLEs Mean: km Max: km Mean: km Max: km

Pg 11 of 17 GLONASS Supplemental TLEs Mean: km Max: km Mean: km Max: km

Pg 12 of 17 Intelsat Comparison IS-6BIS-3RIS-11 IS-6BIS-3RIS-11 Owner ephemerides Public orbital data Supplemental TLEs AFSPC TLEs 43.25° W 43.00° W 42.75° W Spacing = 184 km

Pg 13 of 17 Application: SOCRATES-GEO New system on CelesTrak –Looks for all objects which pass within 250 km of GEO –Uses improved data sources, when available –Generates standard reports, including orbital data –Allows user-defined notification criteria –Automatically sends notification –Web access via secure system

Pg 14 of 17 Data sources Owner ephemeris Public orbital data TLE data Convert to standard format Generate ephemerides Produce enhanced TLEs Select GEO data Data preparation

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Pg 17 of 17 Summary & Conclusions Collaborative effort addresses current limitations –Improves orbital accuracy –Reduces search volumes –Reduces false-alarm rate –Supplements full-catalog orbital data source Reduces SSA tracking requirements –Trust but verify

Questions?